Intellectual Property and Nutrigenomics
Castle, David, Health Law Review
Evidence for the connection between good nutritional regimens and healthy living comes from many quarters: personal testimony, folk wisdom, cross-cultural comparisons, dietetics, naturopathy and other health care modalities, and clinical epidemiology. On the face of it, recommendations to eat fruits and vegetables each day, but not eat a daily pound of butter, are over-determined by available evidence. Yet this might just be literally on the face of it, since many of the strongest associations between diet and heath are based on contestable food recall data paired with phenotypic information drawn from memories, retrospective studies and secondary uses of clinical data. During the short histories of evidence-based medicine and the nutritional sciences this is how it has been: in a sense everyone knows about healthy eating, but explaining what that means in scientific terms has been difficult to achieve.
Two methodological advances in the biological and medical sciences have, since the f950s, dramatically changed the evidence base for understanding diet-health interactions. The first is that the biological and medical sciences have become increasingly experimental, and the second is the shift to a molecular focus. The result is the development of molecular, experimental nutritional sciences, (1) and the advent of the Human Genome Project and molecular genetics. (2) One can now begin to point to causal explanations about the underlying mechanisms that make some diets appear to be healthier than others. More significantly, human genomics and genetics are beginning to reveal how diet and health are linked not only through the physiological activity of nutrients, but that nutrients are involved in the cascade of events beginning with gene regulation and expression.
Nutrigenomics lies at the crossroads of these major developments in the nutritional sciences and human genomics and genetics, and it is also developing at a time when the commercialization of research is an expected outcome of research funding. Technology transfer of bench science to publicly accessible applications is a high priority for universities and their funders who coordinate with private sector companies and investors to bring new products and services to market. Nutrigenomics is a growing field of innovative research and development, it has opened a new field of environmental genomics research, (3) and represents a novel and potentially high-value proposition recognized already by private sector interests. Accordingly, proprietary interest in nutrigenomics has resulted in a number of patents being issued, or existing patents being licensed for use in nutrigenomics applications.
The purpose of this paper is to give an overview of the status of intellectual property rights, particularly patents, in the emerging field of nutrigenomics. It is not a formal and exhaustive review of all nutrigenomics patents, licensing activity, and estimation of market capitalization. Rather, the approach taken here involves the characterization of a few representative patents in nutrigenomics to shed light on the kind of patenting activity in the field. Next follows a discussion about the role of patents in genomics and biotechnology innovation, and highlights some of the claims made about the impact that patents have on innovation and markets. These considerations lead to a short discussion of the impact of patents in nutrigenomics. In recognition of the criticism directed toward patenting in genomics and genetics, this paper concludes with a preliminary evaluation of effects of strategic patent uses in nutrigenomics.
Patenting Activity in Nutrigenomics
There are three main types of conventional patenting activity and one wild-card type that are of interest in nutrigenomics. The three conventional types are: patents on genes, gene variants or methods of detecting gene variants; patents for bioactive food compounds; and patents on proprietary methods for analyzing gene-nutrient associations using computer supported algorithms. …